Interpolation-Dependent Image Downsampling

Interpolation-Dependent Image Downsampling
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插值相关的图像下采样

DOI:
10.1109/tip.2011.2158226
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发表时间:
2011-11
影响因子:
10.6
通讯作者:
Gao, Wen
Gao, Wen
中科院分区:
计算机科学1区
文献类型:
--
作者:
Xiong, Ruiqin;Zhang, Jian;Zhang, Yongbing;Zhao, Debin;Gao, Wen

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传统的图像降采样方法致力于去除混叠伪影。然而,下采样对内插图像质量的影响通常被忽略。为了解决这一问题,本文提出了一种依赖于内插的图像下采样算法(IDID),其中内插依赖于下采样。在给定内插方法的情况下,IDID的目标是获得下采样图像,该下采样图像最小化输入图像与从相应下采样图像内插的图像之间的平方误差和。利用最小二乘算法,得到IDID的解作为上采样的逆算子。我们还为变插值系数的插值法设计了一种依赖于内容的IDID。大量的实验结果证明了IDID算法的可行性和有效性。
Traditional methods for image downsampling commit to remove the aliasing artifacts. However, the influences on the quality of the image interpolated from the downsampled one are usually neglected. To tackle this problem, in this paper, we propose an interpolation-dependent image downsampling (IDID), where interpolation is hinged to downsampling. Given an interpolation method, the goal of IDID is to obtain a downsampled image that minimizes the sum of square errors between the input image and the one interpolated from the corresponding downsampled image. Utilizing a least squares algorithm, the solution of IDID is derived as the inverse operator of upsampling. We also devise a content-dependent IDID for the interpolation methods with varying interpolation coefficients. Numerous experimental results demonstrate the viability and efficiency of the proposed IDID.
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